Fruitful female fecundity after feeding <i>Gryllodes sigillatus</i> royal jelly
Bibliographic record
Abstract
Abstract Dietary honey bee royal jelly increases insect growth rates and adult body size. Royal jelly could enhance mass insect production as a dietary supplement, but it is costly to produce. The mechanisms underlying the effects of royal jelly on growth remain unclear, and so it is valuable to understand the effects of royal jelly on a mass reared model species to try and augment body size in a more cost-effective manner. To determine the effect of royal jelly on a cricket species ( Gryllodes sigillatus ) farmed on mass for human consumption, we ran two experiments. In one experiment we tested the dose-dependent response of Gryllodes sigillatus to royal jelly using a range of diets across 0-30% w/w royal jelly. In another experiment we measured the individual-level life history responses of Gryllodes sigillatus to royal jelly over time by individually rearing freshly-hatched Gryllodes sigillatus on two separate diets: half were fed a commercially available cricket diet, while the other half were fed the same diet mixed with 15% w/w fresh royal jelly. Body size and mass measurements were recorded weekly for five weeks. We found the effects of royal jelly to be sex-dependent within crickets: females fed the royal jelly diet grew to be 30% heavier, and this effect was driven by significantly longer abdomens containing 67% more eggs compared to those fed the basal diet. There was a higher probability of crickets reaching adulthood after 35 days when fed royal jelly, and female mass was optimised at approximately 17% w/w royal jelly. Our results reveal that while a royal jelly dietary supplement can increase the yield of mass-reared insects, the life-history responses are species- and sex-specific.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".